Commercially available image display systems in the medical field utilize various techniques to present image data to a user. Specifically, image data produced within modalities such as Computed Tomography (CT), Magnetic Resonance (MR) and the like is displayed on a display terminal for review by a medical practitioner at a medical treatment site. This image data is used by the medical practitioner to determine the presence or absence of a disease, tissue damage, etc. Through visual comparisons with prior imaging studies, medical practitioners are able to make or improve diagnoses based on changes in a patient's imaging studies over time.
Currently, large volume imaging studies utilized by medical treatment sites, such as CT and MR, pose a significant diagnostic problem due to the large number of image data files that are created and stored for later review. A typical image dataset may easily contain over 2000 slices that translate into a similar number of image data files organized into multiple series. Further, Picture Archiving and Communication Systems (PACS) utilized by medical treatment sites have the ability to present image datasets from multiple modalities, spanning several years. Although the availability of imaging studies from multiple modalities is of benefit to medical practitioners, it is difficult to isolate only relevant prior studies. Further, the amount of data available requires that medical practitioners engage in a time-intensive exercise to filter through studies, series and images, to identify only those that are most relevant to the current diagnosis.
This filtering process is difficult, making an exhaustive comparison of current medical images with a patient's prior history impractical. Moreover, image data is often presented by date. However, medical practitioners are less interested in exact dates than in time periods, for example, the previous quarter or year.